Network monitoring and customer experience monitoring solutions are widely accepted standards for the operations of carrier service provider networks across both fixed networks (e.g., Cable/MSO, IP broadband such as DSL, FITH, etc.) and mobile networks (e.g., 2.5 G, 3 G, LTE, etc.). These systems monitor network traffic via probe devices that collect user and control plane signaling from telecommunication networks, then process that traffic through a variety of stages to derive actionable information as it pertains to subscriber experience (quality of service, quality of experience), subscriber behavior (application usage, service usage, etc.), subscriber location, etc. In practice, actionable information may refer to statistical indicators (typically referred to as Key Performance Indicators or KPIs) that are computed from source data processed by the probes, and then made available to various different user constituents at the carrier for the purpose of driving their business processes.
A few examples of KPIs include Handover Success (by node, location, etc.), Call Drop Ratio (by node, handset, etc.), Application Usage (by node, subscriber, etc.), Subscriber Count (by location, demographic, etc.), and the like.
Quality of Experience (QoE) is a measure of customer's experiences using mobile network services. QoE takes into account the needs and the desires of the subscribers when using a mobile service. For example, an operator may provide reliable data services corresponding to high Quality of Service values, (QoS), but the users may still perceive a low QoE. Since majority of communication problems happen in the radio access network (i.e. RAN) of communication networks, these QoS reports typically do not factor in the impacts of a poor RAN performance due to cell congestion or coverage.
In some wireless communication networks, failures in establishing or maintaining network connection may result in significant degradations in wireless communication performance and quality. Further, in such scenarios, limitations may exist in remedying the degradations. Thus, improvements in handover procedures are desired. Current performance monitoring, optimization and reporting solutions measure the quality of base station handover procedures (e.g., Base Transceiver Station (BTS) handover procedures) based on various levels of network measures of the underlying handover signaling procedures associated with a device, such as perhaps total network handover success, network failures, timeouts or latency metrics. Many of these existing methods and metrics do not necessarily indicate the impact of handovers on the subscriber QoE.
Accordingly, it would be advantageous to provide a more accurate method of detecting and reporting the impact of handovers on subscribers' QoE in a wireless telecommunication network.